Prosecution Insights
Last updated: April 19, 2026
Application No. 18/542,547

SYSTEMS AND METHODS FOR SHARPENING MEDICAL IMAGES

Final Rejection §103
Filed
Dec 15, 2023
Examiner
TSAI, TSUNG YIN
Art Unit
2656
Tech Center
2600 — Communications
Assignee
Stryker Corporation
OA Round
2 (Final)
82%
Grant Probability
Favorable
3-4
OA Rounds
2y 11m
To Grant
93%
With Interview

Examiner Intelligence

Grants 82% — above average
82%
Career Allow Rate
804 granted / 984 resolved
+19.7% vs TC avg
Moderate +11% lift
Without
With
+10.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
31 currently pending
Career history
1015
Total Applications
across all art units

Statute-Specific Performance

§101
3.6%
-36.4% vs TC avg
§103
58.5%
+18.5% vs TC avg
§102
22.8%
-17.2% vs TC avg
§112
4.3%
-35.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 984 resolved cases

Office Action

§103
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Stat of claims: claims 1-34 are pending below. Response to Arguments Applicant's arguments filed 3/16/2026 have been fully considered but they are not persuasive. Applicant remark – (pages 10-11) Applicant stated the claim amendment to claims 1-11 and related system 20-28. Examiner response – Arguments are moot as the new claim amendment has advanced to allowance of claims 1-11 and 20-28. Applicant remark – (pages 10-11) Applicant argued the lack of teaching of new claim amendment such as “determined local contrast based on medical image” and “associated with the respective pixel”. Please see Remarks for further detail. Examiner response – Examiner respectfully disagree. A review of the previous cited prior art Bai et al (US 2011/0125030) in 0038 further detail in 0053-0072, and TODA et al (US 2015/0304524) addresses these new claim amendments in 0061-0062 and 0069. Please see the combine teaching below that addresses the new claim amendments. Please reconsidered amending with object claim language from claims 18-19, that was cited in the previous Office Action, to advance prosecution. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 12 and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Tezaur et al (US 2012/0308154) in view of Bai et al (US 2011/0125030) and further in view of TODA et al (US 2015/0304524). Claim 12: Tezaur et al teaches the following subject matter: A method (0009) for sharpening a medical image comprising: receiving the image (figure 1 and 0024-0025 teaches imaging object such as animal, plants and mammals, structure); and generating a sharpened image, wherein generating the sharpened image comprises, for each pixel of the image (0003-0005 detail sharpening captured images with levels, first, second, third…etc, by means of slops or steps); computing a sharpening value for the respective pixel based on a local contrast associated with the respective pixel and at least one sharpening function (figure 6-7; figure 6 and paragraph 0081-0083 teaches sharpening above with adjusting normalized intensity values with curve slopes, range of the slopes, where range are the threshold from one intensity values to another; figure 7 and 0084 detail using a table with adjusting intensity values (sharpening) with ranges such as up to 0.2, 0.4, 0.6…etc with adjustment factor such as a= 1.2, 1.4, 1.6; 0051-0052 and 0076 addresses sharpening applied areas with different parameter a for less noise for pixel processed). Tezaur et al do not teach the following: determined local contrast based on medical image; medical image. Bai et al (US 2011/0125030) teach: determined local contrast based on medical image (0038 teaches medical imaging such as MRI, X-ray or CT, where 0053 and 0072 detail local contrast of the images for noise removal); receiving the medical image; generating a sharpened medical image from the medical image using at least (0002 teaches medical imaging using ultrasonic diagnostic device, an X-ray device, a CT device and an MRI diagnostic device, where 0013 detail changing the brightness values in the medical image to discontinue strange pattern occurring by using different filters (different sharpening filters)). Tezaur et al and Bai et al are both in the field of image analysis especially switching to appropriate sharpening using brightness values structure elements of interest such that the combine outcome is predictable. Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Tezaur et al by Bai et al such would enhance and smooth for noise removal of the photography image and in order to discontinue strange pattern as disclosed by Bai et al in 0013. Tezaur et al and Bai et al teaches all the subject matter above but do not teach the following: in accordance with the local contrast associated with the respective pixel being positive, using the sharpening value for the respective pixel to increase a brightness value for the respective pixel by a first amount, and in accordance with the local contrast associated with the respective pixel being negative, using the sharpening value for the respective pixel to decrease the brightness value for the respective pixel by a second amount that is less than the first amount would have been had the local contrast been positive. TODA et al (US 2015/0304524) teaches the following subject matter: in accordance with the local contrast associated with the respective pixel being positive, using the sharpening value for the respective pixel to increase a brightness value for the respective pixel by a first amount, and in accordance with the local contrast associated with the respective pixel being negative, using the sharpening value for the respective pixel to decrease the brightness value for the respective pixel by a second amount that is less than the first amount would have been had the local contrast been positive (0061-0062, where 0062 detail ratio of positive to increase brightness, and brightness decrease to lower (decrease), and the amounts are detail in 0061 where one ordinary skill in the art will select that is proper to address the needs/claims requirement; 0069 address how the brightness enhancement ratio to the image due to local contrast sharpen/correcting processing). Tezaur et al and Bai et al and TODA et al are in the field of image analysis, especially sharpness correction processing in image using brightness of local contrast such that the combine outcome is predictable. Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Tezaur et al and Bai et al by TODA et al regarding positive and negative to increase or decrease brightness values such correction processing would provide noise suppression in the respected local contrast to restore input image as disclosed by TODA et al in 0043. Claim 29: Tezaur et al teaches the following subject matter: A system for sharpening a medical image, the system comprising one or more processors, memory, and one or more programs stored in the memory for execution by the one or more processors, wherein the one or more programs include instructions that when executed by the one or more processors cause the system (0029) to: receiving the image (figure 1 and 0024-0025 teaches imaging object such as animal, plants and mammals, structure); and generating a sharpened image, wherein generating the sharpened image comprises, for each pixel of the image (0003-0005 detail sharpening captured images with levels, first, second, third…etc, by means of slops or steps); computing a sharpening value for the respective pixel based on a local contrast associated with the respective pixel and at least one sharpening function (figure 6-7; figure 6 and paragraph 0081-0083 teaches sharpening above with adjusting normalized intensity values with curve slopes, range of the slopes, where range are the threshold from one intensity values to another; figure 7 and 0084 detail using a table with adjusting intensity values (sharpening) with ranges such as up to 0.2, 0.4, 0.6…etc with adjustment factor such as a= 1.2, 1.4, 1.6; 0051-0052 and 0076 addresses sharpening applied areas with different parameter a for less noise for pixel processed). Tezaur et al do not teach the following: determined local contrast based on medical image; medical image. Bai et al (US 2011/0125030) teach: determined local contrast based on medical image (0038 teaches medical imaging such as MRI, X-ray or CT, where 0053 and 0072 detail local contrast of the images for noise removal); receiving the medical image; generating a sharpened medical image from the medical image using at least (0002 teaches medical imaging using ultrasonic diagnostic device, an X-ray device, a CT device and an MRI diagnostic device, where 0013 detail changing the brightness values in the medical image to discontinue strange pattern occurring by using different filters (different sharpening filters)). Tezaur et al and Bai et al are both in the field of image analysis especially switching to appropriate sharpening using brightness values structure elements of interest such that the combine outcome is predictable. Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Tezaur et al by Bai et al such would enhance and smooth for noise removal of the photography image and in order to discontinue strange pattern as disclosed by Bai et al in 0013. Tezaur et al and Bai et al teaches all the subject matter above but do not teach the following: in accordance with the local contrast associated with the respective pixel being positive, using the sharpening value for the respective pixel to increase a brightness value for the respective pixel by a first amount, and in accordance with the local contrast associated with the respective pixel being negative, using the sharpening value for the respective pixel to decrease the brightness value for the respective pixel by a second amount that is less than the first amount would have been had the local contrast been positive. TODA et al (US 2015/0304524) teaches the following subject matter: in accordance with the local contrast associated with the respective pixel being positive, using the sharpening value for the respective pixel to increase a brightness value for the respective pixel by a first amount, and in accordance with the local contrast associated with the respective pixel being negative, using the sharpening value for the respective pixel to decrease the brightness value for the respective pixel by a second amount that is less than the first amount would have been had the local contrast been positive (0061-0062, where 0062 detail ratio of positive to increase brightness, and brightness decrease to lower (decrease), and the amounts are detail in 0061 where one ordinary skill in the art will select that is proper to address the needs/claims requirement; 0069 address how the brightness enhancement ratio to the image due to local contrast sharpen/correcting processing). Tezaur et al and Bai et al and TODA et al are in the field of image analysis, especially sharpness correction processing in image using brightness of local contrast such that the combine outcome is predictable. Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Tezaur et al and Bai et al by TODA et al regarding positive and negative to increase or decrease brightness values such correction processing would provide noise suppression in the respected local contrast to restore input image as disclosed by TODA et al in 0043. Claims 13-17 and 30-34 are rejected under 35 U.S.C. 103 as being unpatentable over Tezaur et al (US 2012/0308154) in view of Bai et al (US 2011/0125030) as applied to claim 12 above, and further in view of Lim et al (US 2016/0037061). Claim 13: Tezaur et al and Bai et al teach teaches all the subject matter above, but do not teach the following: The method of claim 12, wherein the local contrast associated with the respective pixel comprises a signed difference between a luminance and a blurred luminance. Lim et al (US 2016/0037061) teaches the following subject matter: The method of claim 1, wherein the local contrast magnitude comprises an absolute value of a difference between a luminance and a blurred luminance (0082 teaches consideration of absolute difference between brightness (luminance) and blurred of pixel values; 0045 detail such application to local mapping sharpening of luma, with further use of confidence threshold/value for such adjustment as disclosed in 0080 and 0083). Tezaur et al and Bai et al and Lim et al are in the field of image analysis, especially sharpening of local regions of an image using confident values/threshold in regard of brightness/luminance/luma values such that the combine outcome is predictable. Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Tezaur et al and Bai et al by Lim et al regarding using difference between luminance and blurred luminance would provide the best match with confident regarding horizontal shift for adjustment as disclosed by Lim et al in 0082-0083. Claim 14: Tezaur et al teach: The method of claim 12, wherein the at least one sharpening function comprises multiple sharpening functions, each used for a different range of local contrasts (figure 6-7; figure 6 and paragraph 0081-0083 teaches sharpening above with adjusting normalized intensity values with curve slopes, range of the slopes, where range are the threshold from one intensity values to another; figure 7 and 0084 detail using a table with adjusting intensity values (sharpening) with ranges such as up to 0.2, 0.4, 0.6…etc with adjustment factor such as a= 1.2, 1.4, 1.6; 0051-0052 and 0076 addresses sharpening applied areas with different parameter a for less noise for pixel processed). Claim 15: Tezaur et al teach: The method of claim 12, wherein the brightness value is a brightness value for a luminance channel of the medical image (0089 detail the pixel intensity adjustment on each channel with YCbCr color space, and only the Y channel (which represents image luminance) can be sharpened) and Bai et al above teaches medical images. Claim 16: Tezaur et al teach: The method of claim 12, wherein the first amount is defined by a first function and the second amount is defined by a second function that is different than and proportional to the first function (figure 6-7; figure 6 and paragraph 0081-0083 teaches sharpening above with adjusting normalized intensity values with curve slopes, range of the slopes, where range are the threshold from one intensity values to another; figure 7 and 0084 detail using a table with adjusting intensity values (sharpening) with ranges such as up to 0.2, 0.4, 0.6…etc with adjustment factor such as a= 1.2, 1.4, 1.6. One ordinary skill in the art with different sharpening functions would adjust the amount to the sharpening function selected for local processing). Claim 17: Tezaur et al teach: The method of claim 16, wherein the second amount is proportional to the local contrast and to the original brightness value for the respective pixel (figure 6-7; figure 6 and paragraph 0081-0083 teaches sharpening above with adjusting normalized intensity values with curve slopes, range of the slopes, where range are the threshold from one intensity values to another; figure 7 and 0084 detail using a table with adjusting intensity values (sharpening) with ranges such as up to 0.2, 0.4, 0.6…etc with adjustment factor such as a= 1.2, 1.4, 1.6. One ordinary skill in the art with different sharpening functions would adjust the amount to the sharpening function selected for local processing). Claim 30: Tezaur et al and Bai et al teach teaches all the subject matter above, but do not teach the following: The system of claim 29, wherein the local contrast associated with the respective pixel comprises a signed difference between a luminance and a blurred luminance. Lim et al (US 2016/0037061) teaches the following subject matter: The system of claim 29, wherein the local contrast magnitude comprises a signed difference between a luminance and a blurred luminance (0082 teaches consideration of absolute difference between brightness (luminance) and blurred of pixel values; 0045 detail such application to local mapping sharpening of luma, with further use of confidence threshold/value for such adjustment as disclosed in 0080 and 0083). Tezaur et al and Bai et al and Lim et al are in the field of image analysis, especially sharpening of local regions of an image using confident values/threshold in regard of brightness/luminance/luma values such that the combine outcome is predictable. Therefore it would have been obvious to one having ordinary skill before the effective filing date to modify Tezaur et al and Bai et al by Lim et al regarding using difference between luminance and blurred luminance would provide the best match with confident regarding horizontal shift for adjustment as disclosed by Lim et al in 0082-0083. Claim 31: Tezaur et al teach: The system of claim 29, wherein the at least one sharpening function comprises multiple sharpening functions, each used for a different range of local contrasts (figure 6-7; figure 6 and paragraph 0081-0083 teaches sharpening above with adjusting normalized intensity values with curve slopes, range of the slopes, where range are the threshold from one intensity values to another; figure 7 and 0084 detail using a table with adjusting intensity values (sharpening) with ranges such as up to 0.2, 0.4, 0.6…etc with adjustment factor such as a= 1.2, 1.4, 1.6; 0051-0052 and 0076 addresses sharpening applied areas with different parameter a for less noise for pixel processed). Claim 32: Tezaur et al teach: The system of claim 29, wherein the brightness value is a brightness value for a luminance channel of the medical image (0089 detail the pixel intensity adjustment on each channel with YCbCr color space, and only the Y channel (which represents image luminance) can be sharpened) and Bai et al above teaches medical images. Claim 33: Tezaur et al teach: The system of claim 29, wherein the first amount is defined by a first function and the second amount is defined by a second function that is different than and proportional to the first function (figure 6-7; figure 6 and paragraph 0081-0083 teaches sharpening above with adjusting normalized intensity values with curve slopes, range of the slopes, where range are the threshold from one intensity values to another; figure 7 and 0084 detail using a table with adjusting intensity values (sharpening) with ranges such as up to 0.2, 0.4, 0.6…etc with adjustment factor such as a= 1.2, 1.4, 1.6. One ordinary skill in the art with different sharpening functions would adjust the amount to the sharpening function selected for local processing). Claim 34: Tezaur et al teach: The system of claim 33, wherein the second amount is proportional to the local contrast and to the original brightness value for the respective pixel (figure 6-7; figure 6 and paragraph 0081-0083 teaches sharpening above with adjusting normalized intensity values with curve slopes, range of the slopes, where range are the threshold from one intensity values to another; figure 7 and 0084 detail using a table with adjusting intensity values (sharpening) with ranges such as up to 0.2, 0.4, 0.6…etc with adjustment factor such as a= 1.2, 1.4, 1.6. One ordinary skill in the art with different sharpening functions would adjust the amount to the sharpening function selected for local/original processing). Allowable Subject Matter Claims 1-11 are allowed. Please look at the new claim amendment. Claims 20-28 are allowed. Please look at the new claim amendment. Claim 18, and dependent claims 19, are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. At the time of the examination unable to find teaching of claim 18 regarding sharpening of the pixel that is associated with negative local contrast by the requirements of both quotient of: (a) the square of a corresponding brightness value of the medical image, and (b) a difference between the corresponding brightness value of the medical image and the sharpening value. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Gohshi (US 2015/0146995) teaches IMAGE ENHANCEMENT APPARATUS AND IMAGE ENHANCEMENT METHOD – 0012, 0016, 0044, 0068 teaches sharpening input image with first, second and third adjustments, detail use of linear and nonlinear functions on local regions. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to TSUNG-YIN TSAI whose telephone number is (571)270-1671. The examiner can normally be reached 7am-4pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bhavesh Mehta can be reached at (571) 272-7453. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /TSUNG YIN TSAI/Primary Examiner, Art Unit 2656
Read full office action

Prosecution Timeline

Dec 15, 2023
Application Filed
Nov 10, 2025
Non-Final Rejection — §103
Feb 24, 2026
Applicant Interview (Telephonic)
Feb 24, 2026
Examiner Interview Summary
Mar 16, 2026
Response Filed
Mar 24, 2026
Final Rejection — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
82%
Grant Probability
93%
With Interview (+10.9%)
2y 11m
Median Time to Grant
Moderate
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